Complex Functions Research Articles

Holographic complexity in string and M theory

Thus far, the literature regarding holographic complexity almost entirely focuses on the context of (d+1)-dimensional anti–de Sitter spacetime rather than the full higher-dimensional gauge/gravity duality in string or M theory. We provide a framework to study holographic complexity in the full duality, explaining the relation of complexity functionals in the higher-dimensional theory to those in anti–de Sitter spacetime and when complexity functionals can apply universally to gauge/gravity dualities rather than a specific dual pair. We also show that gauge invariance constrains boundary terms for complexity functionals, using the 10- and 11-dimensional supergravity actions as key examples. Finally, we propose new universal complexity functionals following these considerations, including a revised gauge-invariant action complexity. Published by the American Physical Society 2025

Quasi-Babinet principle in dielectric resonators and Mie voids

Advancing resonant nanophotonics requires novel building blocks. Recently, cavities in high-index dielectrics have been shown to resonantly confine light inside a lower-index region. These so-called Mie voids represent a counterpart to solid high-index dielectric Mie resonators, offering novel functionality such as resonant behavior in the ultraviolet spectral region. However, the well-known and highly useful Babinet's principle, which relates the scattering of solid and inverse structures, is not strictly applicable for this dielectric case as it is only valid for infinitesimally thin perfect electric conductors. Here, we show that Babinet's principle can be generalized to dielectric and magnetodielectric systems within certain boundaries, which we refer to as the quasi-Babinet principle and demonstrate for spherical and more generically shaped Mie resonators. Limitations arise due to geometry-dependent terms as well as material frequency dispersion and losses. Thus, our work not only offers deeper physical insight into the working mechanism of these systems but also establishes simple design rules for constructing dielectric resonators with complex functionalities from their complementary counterparts. Published by the American Physical Society 2025

Perspective on the Processing and Functionalities of Solid-State Polyelectrolyte Complexes

Perspective on the Processing and Functionalities of Solid-State Polyelectrolyte Complexes

Stem cell therapies in the clinic

AbstractStem cell therapies have emerged as a transformative approach in modern medicine, with the potential to address and possibly cure a broad spectrum of diseases. These therapies utilize living stem cells that can perform complex biological functions not replicable by traditional drugs. Stem cell therapies have an expanding therapeutic landscape, with several products already approved and numerous clinical trials underway. Among the various stem cell types, hematopoietic stem cells (HSCs) and mesenchymal stem cells (MSCs) are most widely studied. In this review, we provide a detailed analysis of the current clinical landscape of stem cell therapies. We review 27 stem cell products that have received regulatory approvals and discuss 800 ongoing clinical trials, with a focus on HSCs and MSCs. We also discuss the critical challenges to be addressed to facilitate the clinical translation of stem cell therapies.

Regulation of Gut Starvation Responses Through Drosophila NP3253 Neurons.

The "gut-brain axis," a bidirectional communication system between the gastrointestinal tract and the central nervous system, plays a crucial role in regulating complex physiological functions in response to nutrients, pathogens, and microbiota. However, the cellular and molecular mechanisms governing this regulation remain poorly understood. Using Drosophila melanogaster as a model organism, we previously identified NP3253 neurons, located in both the brain and gut, as key contributors to gut homeostasis during oral bacterial infection. Here, we found a novel role of NP3253 neurons in regulating starvation resistance. We observed that a subset of NP3253 neurons in the gut were activated during starvation. To investigate downstream effect, we conducted RNA-Seq analysis on the gut of adult flies with genetically silenced NP3253 neurons, comparing gene expression under starved and fed conditions. This analysis identified 26 genes differentially expressed in response to both starvation and NP3253 neuronal activity. Among these, CG12643, encoding an uncharacterized short peptide, was found to be essential for starvation resistance in the gut. Our findings demonstrate that NP3253 neurons modulate the gut gene expression in response to starvation, thereby supporting physiological adaptation to environmental stressors.

A cluster of patterns for trusted computing

Abstract The proliferation of Internet of Things and cyberphysical systems has introduced unprecedented challenges in ensuring the integrity and confidentiality of critical data, making robust security mechanisms essential. There are several mechanisms intended to assure trust with respect to the software loaded into the system and the trustworthiness of the boot process. These mechanisms start from a Root of Trust (RoT), from where all the other trusts, e.g., for components and software are derived. As part of the RoT, a Secure Storage is needed. This Secure Storage can be considered as part of the RoT or considered a separate component. After a RoT is established, a Trusted Boot can be performed. The execution of computational processes can then be supported by using separate execution zones (Zone Isolation). More complex trust functions such as remote attestation can be performed by a Trusted Platform Module (TPM). In this paper, we propose security patterns for these components. The abstraction power of patterns can be used to define the basic aspects that each of these components must have, thus serving as reference for designers and for security evaluation.

Investigation of 3D circulation and secondary flows in the St. Lawrence Fluvial Estuary at a tidal junction

To enhance understanding of the complex functioning of the St. Lawrence fluvial estuary—a macro-tidal, freshwater estuary located in Quebec, Canada—a 3D numerical model is set up to investigate its hydrodynamics. Validation of the 3D model used field data on water levels, discharge rates, and velocities during both neap and spring tide periods. Comparison of the model with existing 2DH results illustrates the 3D model’s ability to represent the time evolution of the secondary flow during tidal forcing in the confluence/divergence zone around Île d'Orléans. 3D results highlight the great importance of the vertical component of velocity in studying a site with complex geometry. A more detailed analysis of velocities and turbulence at the Île d'Orléans junction shows a time lag of around 1h between current slack and the tidal slack. On the one hand, the current reverses earlier at the bank level than in the deep channel during both ebb and flood periods. On the other hand, the current reverses more quickly at the bottom than at the surface in the main channel. Site geometry, friction and the presence of return currents are the main factors explaining this. This paper highlights the importance of 3D modeling for gaining a deeper understanding of estuarine dynamics, even in the tidal freshwater zone, revealing processes ignored by 2D depth integrated models. Such modeling can assist in planning future field measurement campaigns and improve space-time interpolation methods for velocities in wide estuaries. Additionally, it provides a solid foundation for studying couplings (chemical or particulate) and making predictions, particularly in the context of climate change.

Design of a light and Ca2+ switchable organic–peptide hybrid

The design of organic-peptide hybrids has the potential to combine our vast knowledge of protein design with small molecule engineering to create hybrid structures with complex functions. Here, we describe the computational design of a photoswitchable Ca2+-binding organic-peptide hybrid. The designed molecule, designated Ca2+-binding switch (CaBS), combines an EF-hand motif from classical Ca2+-binding proteins such as calmodulin with a photoswitchable group that can be reversibly isomerized between a spiropyran (SP) and merocyanine (MC) state in response to different wavelengths of light. The MC/SP group acts both as a photoswitch as well as an optical sensor of Ca2+ binding. Photoconversion of the SP to the corresponding MC unmasks an acidic phenol, which CaBS uses as an integral part of both its Ca2+-binding site as well as its tertiary and quaternary structure. By design, the SP state of CaBS is monomeric, while the Ca2+-bound form of the MC state is an obligate dimer, with two Ca2+-binding sites formed at the interface of a domain-swapped dimer. Thus, light and Ca2+ were expected to serve as an "AND gate" that powers a change in backbone structure/dynamics, oligomerization state, and fluorescence properties of the designed molecule. CaBS was designed using Rosetta and molecular dynamics simulations, and experimentally characterized by nuclear magnetic resonance, isothermal titration calorimetry, and optical titrations. These data illustrate the potential of combining small molecule engineering with de novo protein design to develop sensors whose conformation, association state, and optical properties respond to multiple environmental cues.

PH-Controlled DNA Switching Circuits with Multi-State Responsiveness for Logic Computation and Control.

Dynamic control of DNA circuit functionality is essential for constructing chemical reaction networks (CRNs) that implement complex functions. The triplex has been utilized for dynamically regulating the diverse functionalities of DNA circuits due to its distinctive pH responsiveness. However, it is challenging for triplexes to independently regulate the functionality of DNA circuits, as various triplexes were often required for DNA circuits to function in complex environments, which adds complexity to the design and control of dynamic circuits. Here, we proposed a pH-controlled multi-state DNA switching circuit construction strategy to realize dynamic regulation among three states through conformational transitions of the triplex. In addition, by leveraging the regulatory role of multi-state DNA switching circuits on the toehold-mediated strand displacement reaction, we constructed switchable DNA circuits for logic computation and control of hybridization chain reaction (HCR). We confirmed that the designed DNA switching circuits exhibited multi-state responsiveness, allowing for different logical operations at varying pH levels and programmable control of the diverse reaction pathways in the HCR. Our strategy offers a convenient approach for the intelligent response and dynamic regulation of large-scale CRNs and DNA nanostructure self-assembly. It promises applications in biosensing, disease detection and drug delivery.

Scientific and methodological substantiation of key technological parameters, system of criteria and indicators for monitoring and controlling the efficiency of industrial cattle-breeding complexes

The factors and technological parameters of monitoring are generalized and classified, the system of criteria and indicators of effective functioning of industrial cattle-breeding complexes is developed. The directions of improving the assessment of the level and economic efficiency of production intensification at such facilities are substantiated.

Genome-wide identification of the Sec14 gene family and the response to salt and drought stress in soybean (Glycine max)

BackgroundThe Sec14 domain is an ancient lipid-binding domain that evolved from yeast Sec14p and performs complex lipid-mediated regulatory functions in subcellular organelles and intracellular traffic. The Sec14 family is characterized by a highly conserved Sec14 domain, and is ubiquitously expressed in all eukaryotic cells and has diverse functions. However, the number and characteristics of Sec14 homologous genes in soybean, as well as their potential roles, remain understudied.ResultsIn this study, we identified 77 Sec14 genes in the soybean genome that were unevenly distributed across 19 chromosomes. Based on the classification method used for Arabidopsis Sec14 members, GmSec14s can be categorized into three classes: GmPITP1 to GmPITP37, GmSFH1 to GmSFH25, and GmPATL1 to GmPATL15. Structural analysis of the GmSec14 genes revealed that the SFH subfamily contained more introns than the other subfamilies. A total of 10 conserved protein motifs were detected within GmSec14 proteins, with each subfamily possessing unique motifs. Two tandem duplications and 73 segmental duplications were identified among the GmSec14 genes. Additionally, a large number of cis-acting elements, particularly those related to plant hormones, were abundant in the promoter regions of the GmSec14 genes. Tissue expression analysis of the GmSec14 genes indicated that they exhibited distinct tissue-specific expression patterns. In response to salt stress, multiple genes were found to be either upregulated or downregulated. In contrast, the majority of genes were downregulated under drought stress conditions. Notably, 12 GmSec14 genes exhibited significant alterations in expression following salt or drought stress, suggesting a potential role for these genes in stress response mechanisms. Furthermore, the protein interaction network and miRNA regulation associated with GmSec14s were predicted to elucidate the potential functions of GmSec14 members.ConclusionsThis study provides a systematic and comprehensive examination of the Sec14 gene family in soybean, which will facilitate further functional research into their roles in response to salt and drought tolerance.

Advances in biomaterials-based tissue engineering for regeneration of female reproductive tissues.

The anatomical components of the female reproductive system-comprising the ovaries, uterus, cervix, vagina, and fallopian tubes-interact intricately to provide the structural and hormonal support essential for reproduction. However, this system is susceptible to various detrimental factors, both congenital and acquired, that can impair fertility and adversely affect quality of life. Recent advances in bioengineering have led to the development of sophisticated three-dimensional (3D) models that mimic the complex architecture and functionality of reproductive organs. These models, incorporating diverse cell types and tissue layers, are crucial for understanding physiological processes within the reproductive tract. They offer insights into decidualization, ovulation, folliculogenesis, and the progression of reproductive cancers, thereby enhancing personalized medical treatments and addressing female infertility. This review highlights the pivotal role of tissue engineering in diagnosing and treating female infertility, emphasizing the importance of considering factors like biocompatibility, biomaterial selection, and mechanical properties in the design of bioengineered systems. The challenge of replicating the functionally specialized and structurally complex organs, such as the uterus and ovary, underscores the need for reliable techniques that improve morphological and functional restoration. Despite substantial progress, the goal of creating a fully artificial female reproductive system is still a challenge. Nonetheless, the recent fabrication of artificial ovaries, uteruses, cervixes, and vaginas marks significant advancements toward this aim. Looking forward, the challenges in bioengineering are expected to spur further innovations in both basic and applied sciences, potentially hastening the clinical adoption of these technologies.

Neutrophil Engulfment in Cancer: Friend or Foe?

Neutrophils, the most abundant circulating white blood cells, are essential for the initial immune response to infection and injury. Emerging research reveals a dualistic function of neutrophils in cancer, where they can promote or inhibit tumor progression. This dichotomy is influenced by the tumor microenvironment, with neutrophils capable of remodeling the extracellular matrix, promoting angiogenesis, or alternatively inducing cancer cell death and enhancing immune responses. An intriguing yet poorly understood aspect of neutrophil–cancer interactions is the phenomenon of neutrophil engulfment by cancer cells, which has been observed across various cancers. This process, potentially mediated by LC3-associated phagocytosis (LAP), raises questions about whether it serves as a mechanism for immune evasion or contributes to tumor cell death through pathways like ferroptosis. This review examines current knowledge on neutrophil development, their roles in cancer, and the mechanisms of LAP in neutrophil engulfment by tumor cells. We discuss how manipulating LAP impacts cancer progression and may represent a therapeutic strategy. We also explore neutrophils’ potential as delivery vehicles for cancer therapeutic agents. Understanding the complex functions of tumor-associated neutrophils (TANs) and the molecular mechanisms underlying LAP in cancer may open new avenues for effective therapeutic interventions and mitigate potential risks.

Single-cell chromatin accessibility landscape profiling reveals the diversity of epigenetic regulation in the rat nervous system

The mammalian nervous system controls complex functions through highly specialized and interacting structures. Single-cell sequencing can provide information on cell-type-specific chromatin structure and regulatory elements, revealing differences in chromatin organization between different cell types and their potential roles of these differences in brain function. Here, we generated a chromatin accessibility dataset through single-cell ATAC-seq of 174,593 high-quality nuclei from 16 adult rat brain regions. We identified cell subtypes of both neuronal and non-neuronal cells with highly specific distributions and characterized gene regulatory elements associated with cell type-specific regions. To further investigate the gene regulatory network involved in spinal cord regeneration, we integrated our scATAC-seq data with published single-nucleus RNA-seq data from the spinal cord, and we identified more detailed regeneration related elements by drawing GRNs centered on the transcription factor Jun in the OPC. We also performed similar integration analyses in the midbrain. Our findings provide a solid foundation for the comprehensive dissection of the molecular architecture of the mammalian nervous system.

High-stable multifunctional dynamically reconfigurable artificial synapses based on hybrid graphene/ferroelectric field-effect transistors

In response to the challenges posed by traditional computing architectures in handling big data and AI demands, neuromorphic computing has emerged as a promising alternative inspired by the brain's efficiency. This study focuses on three-terminal synaptic transistors utilizing graphene and P(VDF-TrFE) to achieve dynamic reconfigurability between excitatory and inhibitory response modes, which are crucial for mimicking biological functions. The devices operate by applying different top gate spikes (±25 V and ±10 V) to modulate the polarization degree of P(VDF-TrFE), thereby regulating the carrier type and concentration in the graphene channel. This results in the effective realization of enhancement and inhibition processes in two neural-like states: excitatory and inhibitory modes, accompanied by good neural plasticity with paired-pulse facilitation and spike-time-dependent plasticity. With these features, the synaptic devices achieve brain-like memory enhancement and human-like perception functions, exhibiting excellent stability, durability over 1000 cycles, and a long retention period exceeding 10 years. Additionally, the performance of the artificial neural network is evaluated for handwritten digit recognition, achieving a high recognition accuracy of 92.28%. Our study showcases the development of highly stable, dynamically reconfigurable artificial synaptic transistors capable of emulating complex neural functions, providing a foundation for emerging neuromorphic computing systems and AI technologies.

Повышение конкурентоспособности отечественного сельхозмашиностроения посредством управления рисками

The study of competitiveness and risk management issues is currently relevant for many industries and areas of functioning of the agro-industrial complex, including agricultural engineering. The article calculates the level of losses of agricultural engineering enterprises caused by the disparity of economic relations in the agro-industrial complex. Based on this, an assessment is given of the direct and reverse impact of local and industry risks on the functioning of agricultural engineering enterprises, which made it possible to develop a prototype of a risk management system at agricultural engineering enterprises. The study identified the prerequisites for the formation of a harmonious and effective organizational and economic mechanism for the functioning of agricultural engineering enterprises based on a set of scientific approaches. The authors developed a conceptual scheme of the risk management system at agricultural engineering enterprises. The study resulted in proposals for improving the instruments of state regulation of the risk management system of an enterprise in the industry.

MODE: A Web Application for Interactive Visualization and Exploration of Omics Data.

Studies generating transcriptomics, proteomics, lipidomics, and metabolomics (colloquially referred to as "omics") data allow researchers to find biomarkers or molecular targets or understand complex biological structures and functions by identifying changes in biomolecule abundance and expression between experimental conditions. Omics data are multidimensional, and oftentimes summarization techniques such as principal component analysis (PCA) are used to identify high-level patterns in data. Though useful, these summaries do not allow exploration of detailed patterns in omics data that may have biological relevance. The use of interactive HTML displays with plots allows researchers to interact with omics data at a detailed level, but building these displays requires significant coding expertise. To overcome this barrier, the software MODE was built to empower users to build their own interactive HTML displays to support scientific discovery. These displays are easily shareable, do not depend on a specific operating system, and allow users to sort and filter plots by categorical or numerical variables called metas. MODE allows users to build and share these displays with several options for plot design and meta selection. The MODE web application and its capabilities are presented and then demonstrated on lipidomics data from a leaf wounding study.

Dual-Mode ZnO/SnSe Heterojunction Devices with Integrated Bipolar Response Photodetectors and Artificial Optoelectronic Synapses for in-Sensor Computing.

Optoelectronic synapse devices (OESDs) inspired by human visual systems enable to integration of light sensing, memory, and computing functions, greatly promoting the development of in-sensor computing techniques. Herein, dual-mode integration of bipolar response photodetectors (PDs) and artificial optoelectronic synapses based on ZnO/SnSe heterojunctions are presented. The function of the fabricated device can be converted between the PDs and OESDs by modulating the light intensity. As a PD, the polarity of the output current can be switched by tuning the laser wavelength and intensity, which is attributed to the competition between the photovoltaic and photothermoelectric effects in the ZnO/SnSe heterojunction. As an OESD, the device exhibits versatile photonic synaptic characteristics at low light intensity based on the defect-dominant carrier trapping/de-trapping processes, including short/long-term plasticity and learning experience behaviors. More importantly, benefitting from the outstanding synaptic responses, logic functions including "AND" and "OR" are implemented through the in-sensor computing architecture. This work supplies a novel route to realize complex functionality in one device and offers effective strategies for developing in-sensor computing.

3D active-matrix multimodal sensor arrays for independent detection of pressure and temperature.

Pressure and temperature sensing simultaneously and independently is crucial for creating electronic skin that replicates complex sensory functions of human skin. Thin-film transistor (TFT) arrays with sensors have enabled cross-talk-free spatial sensing. However, the thermal dependence of charge transport in semiconductors has resulted in interference between thermal and pressure stimuli. We develop multimodal sensor arrays based on three-dimensional integration of an active matrix to detect temperature and pressure independently. Our approach includes a calibrated compensation to decouple temperature and pressure signals. An individual pixel device consists of a TFT-based pressure sensor layered above a TFT-based temperature sensor. The detected temperature is used to compensate for the thermal effect on TFT-based pressure sensors. We develop large-area sensor arrays to enable accurate detection of two-dimensional pressure and temperature, leveraging these technologies to demonstrate advanced robotic grippers. The grippers stably grasp and lift a cup regardless of temperature, proving their possibility in skin-like electronic applications.

Computational Reconstruction of the Volatility Term Structure in the General Hull–White Model

Volatility recovery is of paramount importance in contemporary finance. Volatility levels are heavily used in risk and portfolio management. We employ the Hull–White one- and two-factor models to describe the market condition. We computationally recover the volatility term structure as a piecewise-linear function of time. For every maturity, a cost functional, defined as the squared differences between theoretical and market prices, is minimized and the respective linear part is reconstructed. On the last time steps, before each maturity, the derivative price is decomposed in order to make the minimization problem analytically solvable. The procedure works fast since only scalar values are obtained on each minimization. However, the predictor–corrector nature of the algorithm allows for the precise recovery of very complex volatility functions. An implicit scheme is used to solve the PDEs on bounded domains. The computational simulations with artificial and real data show that the proposed algorithm is stable, accurate and efficient.